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<?xml version="1.0" encoding="utf-8" ?>
<!DOCTYPE chapter SYSTEM "chapter.dtd">

<chapter>
  <header>
    <copyright>
      <year>2007</year>
      <year>2016</year>
      <holder>Ericsson AB, All Rights Reserved</holder>
    </copyright>
    <legalnotice>
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
 
      http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License.

  The Initial Developer of the Original Code is Ericsson AB.
    </legalnotice>

    <title>The Seven Myths of Erlang Performance</title>
    <prepared>Bjorn Gustavsson</prepared>
    <docno></docno>
    <date>2007-11-10</date>
    <rev></rev>
    <file>myths.xml</file>
  </header>

  <marker id="myths"></marker>
  <p>Some truths seem to live on well beyond their best-before date,
  perhaps because "information" spreads faster from person-to-person
  than a single release note that says, for example, that body-recursive
  calls have become faster.</p>

  <p>This section tries to kill the old truths (or semi-truths) that have
  become myths.</p>

  <section>
    <title>Myth: Tail-Recursive Functions are Much Faster
    Than Recursive Functions</title>

    <p><marker id="tail_recursive"></marker>According to the myth,
    using a tail-recursive function that builds a list in reverse
    followed by a call to <c>lists:reverse/1</c> is faster than
    a body-recursive function that builds the list in correct order;
    the reason being that body-recursive functions use more memory than
    tail-recursive functions.</p>

    <p>That was true to some extent before R12B. It was even more true
    before R7B. Today, not so much. A body-recursive function
    generally uses the same amount of memory as a tail-recursive
    function. It is generally not possible to predict whether the
    tail-recursive or the body-recursive version will be
    faster. Therefore, use the version that makes your code cleaner
    (hint: it is usually the body-recursive version).</p>

    <p>For a more thorough discussion about tail and body recursion,
    see <url href="http://ferd.ca/erlang-s-tail-recursion-is-not-a-silver-bullet.html">Erlang's Tail Recursion is Not a Silver Bullet</url>.</p>

    <note><p>A tail-recursive function that does not need to reverse the
    list at the end is faster than a body-recursive function,
    as are tail-recursive functions that do not construct any terms at all
    (for example, a function that sums all integers in a list).</p></note>
  </section>

  <section>
    <title>Myth: Operator "++" is Always Bad</title>

    <p>The <c>++</c> operator has, somewhat undeservedly, got a bad reputation.
    It probably has something to do with code like the following,
    which is the most inefficient way there is to reverse a list:</p>
    
    <p><em>DO NOT</em></p>
    <code type="erl">
naive_reverse([H|T]) ->
    naive_reverse(T)++[H];
naive_reverse([]) ->
    [].</code>

    <p>As the <c>++</c> operator copies its left operand, the result
    is copied repeatedly, leading to quadratic complexity.</p>

    <p>But using <c>++</c> as follows is not bad:</p>

    <p><em>OK</em></p>
    <code type="erl">
naive_but_ok_reverse([H|T], Acc) ->
    naive_but_ok_reverse(T, [H]++Acc);
naive_but_ok_reverse([], Acc) ->
    Acc.</code>

    <p>Each list element is copied only once.
    The growing result <c>Acc</c> is the right operand
    for the <c>++</c> operator, and it is <em>not</em> copied.</p>

    <p>Experienced Erlang programmers would write as follows:</p>

    <p><em>DO</em></p>
    <code type="erl">
vanilla_reverse([H|T], Acc) ->
    vanilla_reverse(T, [H|Acc]);
vanilla_reverse([], Acc) ->
    Acc.</code>

    <p>This is slightly more efficient because here you do not build a
    list element only to copy it directly. (Or it would be more efficient
    if the compiler did not automatically rewrite <c>[H]++Acc</c>
    to <c>[H|Acc]</c>.)</p>
  </section>

  <section>
    <title>Myth: Strings are Slow</title>

    <p>String handling can be slow if done improperly.
    In Erlang, you need to think a little more about how the strings
    are used and choose an appropriate representation. If you
    use regular expressions, use the
    <seealso marker="stdlib:re">re</seealso> module in STDLIB
    instead of the obsolete <c>regexp</c> module.</p>
  </section>

  <section>
    <title>Myth: Repairing a Dets File is Very Slow</title>

    <p>The repair time is still proportional to the number of records
    in the file, but Dets repairs used to be much slower in the past.
    Dets has been massively rewritten and improved.</p>
  </section>

  <section>
    <title>Myth: BEAM is a Stack-Based Byte-Code Virtual Machine
    (and Therefore Slow)</title>

    <p>BEAM is a register-based virtual machine. It has 1024 virtual registers
    that are used for holding temporary values and for passing arguments when
    calling functions. Variables that need to survive a function call are saved
    to the stack.</p>

    <p>BEAM is a threaded-code interpreter. Each instruction is word pointing
    directly to executable C-code, making instruction dispatching very fast.</p>
  </section>

  <section>
    <title>Myth: Use "_" to Speed Up Your Program When a Variable
    is Not Used</title>

    <p>That was once true, but from R6B the BEAM compiler can see
    that a variable is not used.</p>
  </section>

  <section>
    <title>Myth: A NIF Always Speeds Up Your Program</title>

    <p>Rewriting Erlang code to a NIF to make it faster should be
    seen as a last resort. It is only guaranteed to be dangerous,
    but not guaranteed to speed up the program.</p>

    <p>Doing too much work in each NIF call will
    <seealso marker="erts:erl_nif#WARNING">degrade responsiveness
    of the VM</seealso>. Doing too little work may mean that
    the gain of the faster processing in the NIF is eaten up by
    the overhead of calling the NIF and checking the arguments.</p>

    <p>Be sure to read about
    <seealso marker="erts:erl_nif#lengthy_work">Long-running NIFs</seealso>
    before writing a NIF.</p>
  </section>
</chapter>